Medical Knowledge Integration Into Reinforcement Learning Algorithms for Dynamic Treatment Regimes
Summary The goal of precision medicine is to provide individualised treatment at each stage of chronic diseases, a concept formalised by dynamic treatment regimes (DTR). These regimes adapt treatment strategies based on decision rules learned from clinical data to enhance therapeutic effectiveness.
Sophia Yazzourh +3 more
wiley +1 more source
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
Conversational AI Agents: The Effect of Process and Outcome Variation on Anthropomorphism and Trust
ABSTRACT Organisations increasingly deploy conversational AI agents (CAs) in agentic roles where behavioural variations are inevitable. Prior work often conflates two distinct forms of variation: outcome variation (where success fluctuates) and process variation (where the path to completion varies).
Kambiz Saffarizadeh, Mark Keil
wiley +1 more source
Breeding 5.0: Artificial intelligence (AI)‐decoded germplasm for accelerated crop innovation
ABSTRACT Crop breeding technologies are vital for global food security. While traditional methods have improved yield, stress tolerance, and nutrition, rising challenges such as climate instability, land loss, and pest pressure now demand new solutions.
Jiayi Fu +4 more
wiley +1 more source
Do robots boost productivity? A quantitative meta‐study
ABSTRACT This meta‐study analyzes the productivity effects of industrial robots. More than 1800 estimates from 85 primary studies are collected. The meta‐analytic evidence suggests that robotization has so far provided, at best, a small boost to productivity. There is strong evidence of publication bias in the positive direction.
Florian Schneider
wiley +1 more source
Revisiting the Health Spending‐Growth Nexus
ABSTRACT The relationship between health spending and economic growth is shaped by multiple transmission channels, leading to inconsistencies in the empirical literature and a lack of definitive conclusions. To address this issue, we perform a meta‐analysis encompassing 522 estimates from 107 studies that examine the effect of health spending on ...
Andreas Sintos +2 more
wiley +1 more source
From gateway to value ladder—The curious case of online mutual aid in China
Abstract This study examines how InsurTech‐enabled information provision, specifically the disclosure of claimant information previously unavailable in conventional insurance, influences individuals' insurance uptake. We leverage Mutual Aid (MA) platforms as a natural context to examine how socially framed loss information, peer influence, and salience
Ze Chen +3 more
wiley +1 more source
SEMI-MARKOV DECISION PROCESSES WITH COUNTABLE STATE SPACE AND COMPACT ACTION SPACE
We shall be concerned with the optimization problem of semi-Markov decision processes with countable state space and compact action space. Defined is the generalized reward function associated with the semi-Markov decision processes which include the ordinary discounted Markov decision processes of discrete time parameter and also the continuous time ...
openaire
A perspective on automated rapid eye movement sleep assessment
Summary Rapid eye movement sleep is associated with distinct changes in various biomedical signals that can be easily captured during sleep, lending themselves to automated sleep staging using machine learning systems. Here, we provide a perspective on the critical characteristics of biomedical signals associated with rapid eye movement sleep and how ...
Mathias Baumert, Huy Phan
wiley +1 more source
Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models
ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley +1 more source

